| Qualification Type: | PhD |
|---|---|
| Location: | Exeter |
| Funding for: | UK Students, EU Students, International Students, Self-funded Students |
| Funding amount: | For eligible students the studentship will cover home tuition fees plus an annual tax-free stipend. |
| Hours: | Full Time |
| Placed On: | 17th November 2025 |
|---|---|
| Closes: | 8th January 2026 |
| Reference: | 5753 |
About the Partnership
This project is one of a number that are in competition for funding from the NERC Great Western Four+ Doctoral Training Partnership (GW4+ DTP). The GW4+ DTP consists of the Great Western Four alliance of the University of Bath, University of Bristol, Cardiff University and the University of Exeter plus five Research Organisation partners: British Antarctic Survey, British Geological Survey, Centre for Ecology and Hydrology, the Natural History Museum and Plymouth Marine Laboratory. The partnership aims to provide a broad training in earth and environmental sciences, designed to train tomorrow’s leaders in earth and environmental science. For further details about the programme please see http://nercgw4plus.ac.uk/
For eligible successful applicants, the studentships comprises:
Project Aims and Methods
In this project we want to provide a better understanding of how cloudiness affects, and is affected by, environmental factors called “cloud controlling factors”. Success of this goal will be of benefit to a wide range of scientific communities, because the interactions of clouds with the mean climate is consistently the most difficult aspect of climate change to estimate correctly. To this end we will apply nonlinear and associational (colloquially called “causal”) timeseries analysis techniques to provide a more rigorous, and more statistically significant framework for understanding the connections between clouds and climate. Ultimately, we want to create to causal graphs for large-scale cloudiness, its dependence, and its effect on the related environmental factors. Additional or alternative statistical and data analysis frameworks are welcomed to be proposed or developed by the candidate as part of the project. We will apply the methodologies to a wide range of data from observations to modelling output, in collaboration with the project partners in the MetOffice and Lawrence Livermore National Laboratory.
The candidate will receive expert training on data analysis, timeseries analysis, Julia software development, and time management. The candidate will regularly visit the MetOffice for scientific exchanges and data acquisition.
Useful recruitment links:
For information relating to the research project please contact the lead Supervisor via: g.datseris@exeter.ac.uk
Collaborative Partner
The Met Office will provide data, research visits, computational resources and a potential internship.
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